Figure 1
PRISMA flow diagram (Adapted from the PRISMA 2020 statement https://www.prisma-statement.org/prisma-2020).
Figure 2
Conceptual framework illustrating the integration of AIoT, HVAC optimisation, occupant comfort, and building automation in smart buildings (adapted from (Himeur, et al., 2023).
Table 1
Overview of key AIoT technologies and their applications in smart building energy management.
| TECHNOLOGY | APPLICATION AREA | FUNCTIONALITY | REFERENCE |
|---|---|---|---|
| Occupancy Sensors | HVAC/Lighting Control | Detect presence, optimise schedules | (Kim, et al., 2023) |
| Temperature/Humidity Sensors | Environmental Monitoring | Maintain thermal comfort | (ASHRAE, 2020a) |
| CO2/VOC Sensors | Indoor Air Quality | Trigger ventilation | (Bourikas, et al., 2021) |
| Smart Meters | Energy Management | Track consumption, identify savings | (Gupta and Kotopouleas, 2018) |
| Machine Learning | Predictive Control | Forecast demand, optimise setpoints | (Markowitzand Drenkow, 2024) |
| Digital Twins | Performance Simulation | Real-time monitoring & optimisation | (Rutkowski, et al., 2024) |
Table 2
Selected exemplary case studies of AIoT-enabled energy efficiency strategies in smart buildings (adapted from (Dankan Gowda et al., 2024; Pang et al., 2024; Rutkowski et al., 2024).
| BUILDING TYPE | AIOT SOLUTION | MAIN OUTCOME | REFERENCE |
|---|---|---|---|
| Smart Home | Cloud-integrated AIoT | 18% energy savings | (Gowda, et al., 2024) |
| Multi-family | Intelligent EMS | 15% reduction in HVAC use | (Amma Oforiwaa Ampomah-Asiedu and Wepea Adamwaba Buntugu, 2024) |
| Apartment | Occupancy Sensing | 20% HVAC energy savings | (Pang, et al., 2024) |
| Multi-family | Digital Twin | Improved performance tracking | (Rutkowski, et al., 2024) |
| Server Room | AI-driven CFD | Optimised airflow, reduced energy | (Carlsson, 2024) |